Ex-post Analysis Research Articles

Red flag behaviors in financial services frauds: a mixed-methods study

PurposeThis study aims to enlist the red flag behaviors exhibited in financial services frauds.Design/methodology/approachA pluralistic mixed methodology was adopted in this study. Data collected via semi-structured interviews were coded, quantified and subjected to descriptive analysis to identify the most frequently exhibited red flag behaviors in financial services frauds. The relative risk of exhibition of the identified red flag behaviors was assessed by intuitively comparing the red flag behaviors identified in financial services frauds (experimental group, n = 24) with the red flag behaviors identified in a heterogeneous control sample of non-financial services frauds (control group, n = 28).FindingsThis study identifies six red flag behaviors likely to be more frequently exhibited in financial services frauds than in non-financial services frauds.Practical implicationsResults of this study can be used to develop a typical behavioral profile of a financial services fraud perpetrator. Active communication of this profile in fraud awareness training can help make fraud conspicuous in the financial services industry.Originality/valueThis study is unique because human behavior as a possible fraud indicator is an under-researched area. Further, this study examines first level of evidence and attempts an ex-post analysis of actual red flag behaviors exhibited in acknowledged fraud cases in which the perpetrator/perpetrators has/have been clearly identified.

Comparative evaluation of investment analysis methods: an application in renewable energy auctions between 2011 e 2015

Purpose - This work aims to analyze the assertiveness of net present value (NPV) and real options theory (ROT), at the moment of decision making for investments in renewable energy projects, considering the 244 winning projects in the auctions of reserve energy that occurred between 2011 and 2015.Design/methodology/approach –This is a quantitative study that used real data from 150 wind power and 94 photovoltaic projects available on ANEEL´s website. For data analysis, the confusion matrix, the area under the ROC Curve and the Kappa Index were used.Findings – It was concluded that NPV is more effective for recommendations to invest in projects with chances to be successful, while ROT is more accurate in suggesting against investing in projects with propensity for failure. It was also found that the degree of agreement between the two techniques is substantial and determined by the level of volatility of real options.Research limitations/implications – The limitations of this study refer to the difficulties of identifying the reasons that motivated failures in the projects.Originality/value – Theoretically, this work contributes to identify the characteristics that effectively differentiate ROT from NPV at the time of decision making. Empirically, this work contributes to doing an ex-post analysis of the projects.

Economic benefits through system integration of electric waste collection vehicles: Case study of grid-beneficial charging and discharging strategies

Electrification of a waste collection fleet as part of vehicle-to-grid can be used in a grid- beneficial way, which in turn can increase the economy of these vehicles. In this study the system and grid integration of fully battery-electric waste collection vehicles (eWCV) is examined. The possibility to shave power peaks of a lightweight packaging plant and to provide balancing power by eWCV are analyzed. For this, performance and market models are developed using an ex-post analysis, considering also levies and charges. Building on this, various scenarios for the grid-beneficial integration of eWCV are designed. These are assessed based on the resulting energy consumption of the eWCV, charging costs and feasibility for real-life implementation. It is shown that using electricity generated by thermal waste management plants for charging can reduce the operation costs of eWCV. Also, peak shaving is viable from an economic point of view. Network charges and well as the complexity of the system prevent an economical provision of balancing power by eWCV.

Using energy saving deficit distributions to assess calculated, deemed and metered electricity savings estimations

Energy efficiency programme monitoring is often based on ex-ante saving estimations. These estimations lack standardization, are prone to parameter errors, and neglect rebound effects. Moreover, a comparison with ex-post estimations is not systematically done. This paper proposes a simple methodology to assess ex-ante against ex-post estimations, using the distribution of the energy savings deficit, i.e. the normalized difference between reported and metered savings. This methodology is applied to a dataset of lighting renovation measures to first assess calculated savings against utility meter data. The mean energy savings deficit amounts to 39% for measures in small to medium enterprises and to 28% in common areas of buildings. Further analysis shows that this overestimation arises from both significant calculation errors and rebound effects. These analysis and findings are the first of their kind for these sectors. The methodology is further used to assess deemed savings approaches. The results show that coefficients based on time-of-use and the type of replaced technology provide a precision comparable to calculated savings. Further limitations of ex-ante quantitative monitoring are identified based on empirical observations of a utility-driven programme. This suggests that, instead of current practices, quantitative monitoring should focus on ex-post analysis of meter data. This would free up resources for a more qualitative follow-up of measure impacts to better inform programme and policy design.

Cross-leveraging synergistic benefits from across an event portfolio: Empirical evidence from Madeira

While most tourism destinations host a range of events, these are often planned and delivered without explicit reference to one another. There may, however, be benefits to recognising the potential inter-relatedness of events in a destination and developing synergies between them. This study analyses a calendar of events based in Madeira, Portugal, to identify areas of relatedness that could be cross-leveraged by managing and marketing the events as a strategic portfolio. Accordingly, a questionnaire was administered among attendees at five major events, yielding 3118 responses. These data were analysed using ANOVA and two types of regression. The results suggest that, firstly, it is prudent to employ a range of analytical techniques to the available data to identify appropriate strategic levers. Secondly, the findings demonstrate the potential for post-hoc analysis not only to identify areas of relatedness between the events but also to discover gaps that can be filled by new events. Thirdly, the findings emphasise the pivotal role that destination marketing organisations can play in facilitating the design and implementation of event portfolio strategies based on the cross-leveraging of areas of relatedness between the events. • Relatedness assists the cross-levering of synergies within an events portfolio. • Ex-post analysis is a viable means of identifying such synergies. • Various analytical techniques preferable to determine potential cross-leverage. • Similar audience demographics between events in a portfolio enhances relatedness. • Attendee satisfaction is dependent mainly on the quality of event programme content.

Risk blindness in local perspectives about the Alberta oil sands hinders Canada's decarbonization

Local perspectives can conflict with national and international climate targets. This study explores three stakeholder (community, provincial, and federal) perspectives on the Alberta oil sands as risks for a sustainability transition in Canada. In an ex-post analysis, we compared outputs from stakeholder consultations and energy-economy models. Our research shows that different local stakeholders groups disregarded some policy risks for the Alberta oil sands and Canadian energy transition. These stakeholders expected the sector to grow, despite increasing environmental penalties and external market pressures. The study revealed that blind-spots on risks, or “risk blindness”, increased as stakeholders became less certain about policy climate goals. We argue that “risk blindness” could be amplified by dominant institutional narratives that contradict scientific research and international climate policy. Strategies that integrate local narratives, considered as marginalized, provide perspectives beyond emission reductions and are essential for meeting climate targets while supporting a just transition.

Learning model of municipal students

This study aims to analyze the learning model of municipal students. The approach used in this study is a quantitative correlational study with an ex-post facto design and path analysis. The instrument used is a questionnaire and Structural Equation Modeling (SEM) with WarpPLS 4.0 statistical software to analyze the data. The results show that there are positive and significant effects of self-confidence on learning motivation, and the effects of learning style are also positive and significant on learning motivation. There is a positive and significant effect of parent encouragement on learning motivation. The effect of student’s self-confidence on learning motivation also shows positive and significant. The impact of learning motivation on learning outcomes is significantly positive. While the impact of self-confidence on learning outcomes also shows positive results. The effect of parental encouragement on learning outcomes. Finally, the effect of parental encouragement on self-confidence also describes positive impacts. 
 
 Keywords: Learning Model, Students, Municipal, Self-confidence, Learning Motivation, Learning Outcomes

The heterogeneity of European Higher Education Institutions: a configurational approach

ABSTRACT Classifications are a basic tool for research, which allow summarizing the diversity of objects in a number of categories that fits the cognitive abilities of the human mind. Their relevance for higher education is emphasized by the differentiation of institutional profiles. Yet, unlike in the US, there is currently no classification of European Higher Education Institutions (HEIs). This paper fills this gap by developing a classification of European HEIs, which focuses on differences in activity profiles and subject scope. To this aim, it uses data from an enriched version of the European Tertiary Education Register on a sample of more than 2000 HEIs in a large number of European countries. The classification comprises six classes that occupy distinct positions in a configuration space defined by two dimensions, i.e. research vs. educational orientation and subject specialization. Ex-post analysis shows that classes are identifiable and can be attributed meaningful labels; the class of research universities comprises most European HEIs competing in international rankings, while a class of generalist HEIs with lower research orientation that cuts across the traditional distinction between universities and Universities of Applied Sciences can be distinguished. Furthermore, three classes of specialist HEIs can be identified. The classification provides a meaningful representation of European higher education that is more fine-grained than the distinction between university and non-university sectors while remaining parsimonious. We, finally show how national categories map to the classification, displaying its potential to compare differences in national institutional settings across Europe.

How to Improve Effectiveness of Renewable Space Heating Programs by Better Understanding Homeowner—Installer Interactions

In this paper, we perform a literature review on the current state of knowledge about homeowners in the context of the adoption of renewable heating systems. Despite a considerable number of studies about homeowners, homeowner–installer interactions, and ways to improve the effectiveness of renewable heating programs, based on homeowner knowledge, have not yet been studied in much detail. To address these knowledge gaps, we conduct a qualitative study on single-family house owners who installed heat pumps and took part in a renewable heating program in Geneva, Switzerland. We cover homeowner practices in choosing installers and heating system types, homeowners’ feedback about heat pump installation and use, as well as their experience in participation in the renewable heating program. Based on the literature review and the findings from the interviews, we provide the following recommendations on how to increase the effectiveness of renewable heating programs: (a) support for homeowners should not be limited to financial incentives; (b) partnership programs with installers could help to increase the quality of installation services and enable homeowners to choose qualified installers; and (c) assisting homeowners in pre-qualification and ex-post analysis, in learning how to operate their renewable heating systems and in solving problems during the post-installation period, can contribute to improved technology reputation, which can, in turn, increase technology uptake by other homeowners.

Teleworking and Online Shopping: Socio-Economic Factors Affecting Their Impact on Transport Demand

Teleworking and online shopping became commonplace during the COVID-19 pandemic and can be expected to maintain a strong presence in the foreseeable future. They can lead to significant changes in mobility patterns and transport demand. It is still unclear, however, how extensive their adoption can be, since each individual has different preferences or constraints. The overall impact on transport depends on which segments of the population will modify their behaviour and on what the substitutes to the current patterns will be. The purpose of this work is to identify the user profiles and spatial aspects that affect the adoption of teleworking and online shopping, and to explore the potential impact on transport demand. To that end, data from an EU-wide survey on mobility were analysed using a Machine Learning methodology. The results suggest that while the take up of the new work and consumption patterns is high on average, there are significant differences among countries and across different socio-economic profiles. Teleworking appears to have a high potential mainly in certain services sectors, affecting commuting patterns predominantly in large urban areas. Online shopping activity is more uniform across the population, although differences among countries and age groups may still be relevant. The findings of this work can be useful for the analysis of policies to encourage the uptake of new technologies in transport and mobility. They can be also a good reference point for future studies on the ex-post analysis of the impacts of the pandemic on mobility.

Estimation of Large Household Appliances Stock in the Residential Sector and Forecasting of Stock Electricity Consumption: Ex-Post and Ex-Ante Analyses

Energy efficiency offers a wide variety of opportunities that will provide efficient resource utilization, alleviate the pressure of energy costs on the economy and reduce foreign energy dependency, and support in combating the harmful effects of climate change. This paper aims to develop necessary data sets to guide policymakers in their decision-making process to identify energy efficiency policy options through an ex-post analysis. One of the targets of this paper is to determine the large household appliances stock and its electricity consumption, which constitutes an important share in residential electricity consumption over the period of 2005-2019. In light of the findings from the ex-post analysis, electricity consumption scenarios for large household appliances were developed from 2020 to 2030. According to the results, the total stock consumption of the refrigerator and washing machine appliances has reached a plateau, leaving behind an increasing trend due to the improvements in efficiency despite the growth in the stock amounts. Besides, the electricity consumption of freezer, tumble dryer, and dishwasher stock has increased significantly due to the increase in the household ownership rates. The analyses also showed that the total electricity consumption of the large household appliances’ stock increased from 17,973 GWh in 2005 to 23,067 GWh in 2019. In addition, the ex-ante analysis revealed that the electricity consumption of refrigerator stock would show most likely a downward trend until 2030, while deep freezers, tumble dryers, dishwashers, and electric ovens stocks would demand more electricity with the increase in ownership rates. However, the analysis showed an uncertain pathway for the electricity consumption of washing machine stock since annual sales during the projection period would show in which direction their consumption would evolve.

Urban Design and the Role of Placemaking in Mainstreaming Nature-Based Solutions. Learning From the Biblioteca Degli Alberi Case Study in Milan

Nature-based solutions' (NBS) relevance for tackling environmental challenges has been on the frontiers of urban regeneration mechanisms since the beginning of the 2010s. There is an increasing interest in applying NBS in urban planning and design to build support and engagement for sustainable urban development. However, NBS's operational use as deliberate design interventions is not widely reflected in the scientific discourse, more evidence is needed on how functional and viable aspects of urban nature can be conceptualized in urban design. This calls to explore the ways urban design can advance their understanding as part of place-specific, designed urban spaces. Through an ex-post analysis, the authors examined the design and implementation process of an exemplary NBS project, the Biblioteca degli Alberi park in Milan, part of one of the largest, recent urban regeneration projects in Europe. In a synthetic analysis, design drivers, enablers, and deficiencies are discussed, which affect the park's performance both from human-centered and nature-based perspectives. The park's case demonstrates design actions and considerations affecting all stages of the life-cycle of an NBS, from the creative design phase to the development, use, and management phases, and how urban design can create conditions for amplifying the multifunctional potential of urban ecosystems. The results highlight the importance of integrating an urban ecology perspective in the entirety of the design process when implementing NBS, consequently for a successful re-scoping of urban design and planning practices to infuse human-centeredness with “nature-basedness.”

The Impact of Renewable Energy Generation on the Spot Market Price in Germany: Ex-Post Analysis using Boosting Method

This study combines regression analysis with machine learning analysis to study the merit order effect of renewable energy focusing on German market, the largest market in Europe with high renewable energy penetration. The results show that electricity from wind and solar sources reduced the spot market price by 9.64 €/MWh on average during the period from 2010 to 2017. Wind had a relatively stable impact across the day, ranging from 5.88 €/MWh to 8.04 €/MWh, while the solar energy impact varied greatly across different hours, ranging from 0.24 €/MWh to 11.78 €/MWh and having a stronger impact than wind during peak hours. The results also show characteristics of the interactions between renewable energy and spot market prices, including the slightly diminishing merit order effect of renewable energy at high generation volumes. Finally, a scenario-based analysis illustrates how different proportions of wind and solar energies affect the spot market price

Predicting Influential Users in Online Social Network Groups

The widespread adoption of Online Social Networks (OSNs), the ever-increasing amount of information produced by their users, and the corresponding capacity to influence markets, politics, and society, have led both industrial and academic researchers to focus on how such systems could be influenced . While previous work has mainly focused on measuring current influential users, contents, or pages on the overall OSNs, the problem of predicting influencers in OSNs has remained relatively unexplored from a research perspective. Indeed, one of the main characteristics of OSNs is the ability of users to create different groups types, as well as to join groups defined by other users, in order to share information and opinions. In this article, we formulate the Influencers Prediction problem in the context of groups created in OSNs, and we define a general framework and an effective methodology to predict which users will be able to influence the behavior of the other ones in a future time period, based on historical interactions that occurred within the group. Our contribution, while rooted in solid rationale and established analytical tools, is also supported by an extensive experimental campaign. We investigate the accuracy of the predictions collecting data concerning the interactions among about 800,000 users from 18 Facebook groups belonging to different categories (i.e., News, Education, Sport, Entertainment, and Work). The achieved results show the quality and viability of our approach. For instance, we are able to predict, on average, for each group, around a third of what an ex-post analysis will show being the 10 most influential members of that group. While our contribution is interesting on its own and—to the best of our knowledge—unique, it is worth noticing that it also paves the way for further research in this field.

A hybrid approach to discern customer experience for facilitating the adoption of smartwatches

ABSTRACT Smartwatches had been anticipated to gain momentum as a daily device regarded as a fashion accessory. Contrary to expectations, the pace of adoption rate is slowing down and no one can deny that smartwatches currently fall into a ‘chasm’. This research focuses on the customer experiences accumulated in textual form on ‘Amazon.com’ and attempts to reorganise the influential constructs affecting the adoption of smartwatches. To this end, we conduct a hybrid approach that integrates a qualitative and quantitative approach. First, the apparent constructs are identified and categorised through an exhaustive review of the latest research. Second, LDA-based topic modelling is applied to uncover customers’ topics consisting of contextually associated terms. Comparing with the apparent constructs, we discover two newly emerging constructs: ‘relative superiority’ and ‘consumer rights’. Third, ex-post analysis is performed to acquire greater depth and breadth in understanding human desires inherent in each construct. Based on a total of 12 key constructs, 5 human desires are proposed as a result and discussed to support the establishment of R&D planning and marketing strategies.

Energy Effectiveness or Economic Profitability? A Case Study of Thermal Modernization of a School Building

Thermal refurbishment of buildings results in certain energy, financial, and environmental effects. Such investments are financially supported in Poland after meeting the legally defined conditions of thermal protection and energy consumption. This paper presents a complex thermal modernization of a school building, performed by following Polish regulations. A detailed description of the studied object was given, and the calculation procedure was described. Then an optimal variant of an investment and an ex-post analysis were described. Simple payback time (SPBT) of modernization measures was from 15.8 years (insulation of the ceiling under the unheated attic) to 87 years for insulation of the wooden external wall, with 35.6 years for the whole project, which is shorter than the predicted lifespan of the whole building (50–70 years). Annual calculated heating demand decreased from 464.78 to 168.73 GJ, resulting in the primary energy consumption indicator (EP) of 484.44 and 129.46 kWh/m2, respectively. Thermal refurbishment with the replacement of an old boiler into a new wood-pellet one resulted in a significant reduction of SO2 and dust emissions from 451 to 27.5 kg and from 399 to 13 kg, respectively.

The Five Attribute Performance Assessment (FAPA) model to evaluate the performance of an urban consolidation centre

Nowadays, local authorities are not completely aware of the advantages of city logistics measures, as they usually do not have a quantitative estimation of their related benefits. One of the most popular city logistics schemes is probably the Urban Consolidation Centre, which aims to reduce the number of freight movements in urban areas through consolidation of goods and optimisation of deliveries. Due to its potential to reduce the negative impact of urban freight transport, the consolidation centre has been widely supported by local, national, and European authorities. However, there is a lack of performance evaluation (ex-post analysis) and little research on methods and tools to evaluate and quantify the actual benefits. This research work proposes a model based on a set of indicators that allow assessing the efficiency and effectiveness of an Urban Consolidation Centre in terms of costs, time, quality, productivity, and environmental sustainability. Ex-ante and ex-post evaluations are performed through a case study approach to validate the model. Results show that the model is suitable to both applications and can be customised to deliver tailored performance evaluations.

Portfolio optimization using higher moments in an uncertain random environment

In this paper, a multi-objective portfolio optimization problem is studied in an uncertain random environment using higher moments. We consider a scenario involving an asset universe wherein some assets have sufficient historical return data for modelling as random variables, and others, listed relatively recently, lack historical data. The asset returns of such assets are modelled as uncertain variables. Thus, a hybrid environment involving both uncertain and random variables is considered. We use mean absolute semi-deviation as a risk measure and employ skewness (i.e., third moment) in the portfolio optimization model. The expressions for the mean absolute semi-deviation and skewness of an uncertain random variable have been derived. We show that the derivation of mean absolute semi-deviation is not based on any stipulation and thus is an accurate measure of risk (unlike the variance of an uncertain random variable, which uses stipulation). We propose a hybrid genetic algorithm as a solution methodology and provide empirical proofs to illustrate its advantages. The proposed methodology has been applied to a case study involving 100 assets listed in the NASDAQ-100 index of the U.S. stock market. We do an ex-post analysis to track the performance of our model out-of-sample and illustrate its advantages.

Screening for Plasminogen Mutations in Hereditary Angioedema Patients.

Hereditary angioedema (HAE) is a rare disease belonging to the group of bradykinin-mediated angioedemas, characterized by recurring edematous episodes involving the subcutaneous and/or submucosal tissues. Most cases of HAE are caused by mutations in the SERPING1 gene encoding C1-inhibitor (C1-INH-HAE); however, mutation analysis identified seven further types of HAE: HAE with Factor XII mutation (FXII-HAE), with plasminogen gene mutation (PLG-HAE), with angiopoietin-1 gene mutation (ANGPT1-HAE), with kininogen-1 gene mutation (KNG1-HAE), with a myoferlin gene mutation (MYOF-HAE), with a heparan sulfate-glucosamine 3-sulfotransferase 6 (HS3ST6) mutation, and hereditary angioedema of unknown origin (U-HAE). We sequenced DNA samples stored from 124 U-HAE patients in the biorepository for exon 9 of the PLG gene. One of the 124 subjects carried the mutation causing a lysine to glutamic acid amino acid exchange at position 330 (K330E). Later, the same PLG mutation was identified in the patient’s son. The introduction of new techniques into genetic testing has increased the number of genes identified. As shown by this study, a biorepository creates the means for the ex-post analysis of recently identified genes in stored DNA samples of the patients. This makes the diagnosis more accurate with the possibility of subsequent family screening and the introduction of appropriate therapy.

Wind power projects in Brazil: challenges and opportunities increasing co-benefits and implications for climate and energy policies

The purpose of this article is to analyze the challenges to, and opportunities for, increasing sustainable development (SD) co-benefits delivered by clean development mechanism (CDM) wind power projects in northeastern Brazil and the resulting implications for climate and energy policies. Five methodological phases were met: First, a documentary research was conducted in the main CDM database; second was a literature review, creating the analytical framework and a survey questionnaire needed to assess the SD co-benefits from the projects; third, documentary research was used to enable ex-ante analysis of the SD co-benefits proposed in the CDM Project Design Documents (PDDs); fourth, survey allowed for the analysis of SD co-benefits perceived by project entrepreneurs (ex-post analysis); and finally, a comparison between the ex-ante and ex-post analyses was completed. The results show the importance of carrying out SD co-benefit studies after the implementation of CDM projects in order to learn lessons for new mechanisms of climate governance. The lowest SD co-benefits were water management improvement in the project influence area, soil pollution prevention, health and safety improvements and technology transfer. The greatest opportunities for increasing SD co-benefits come from the environmental licensing process and the strengthening of Corporate Social Responsibility. The greatest challenges are new technology development, stakeholders’ engagement and SD co-benefit audits. We conclude that the improvement of multi-level climate and energy governance plays a key role in increasing SD co-benefits.